A lymphocyte-cytokine network inspired algorithm for data analysis

Yang Liu*, Jon Timmis, Tim Clarke

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

Abstract

In this paper, we propose an algorithm for cluster analysis inspired by the lymphocyte-cytokine network in the immune system. Our algorithm attempts to optimally represent a large data set by its principle subset whilst maximising the data kernel density distribution. Experiments show that the output data set created by our algorithm effectively represents the original input data set, according to the Kullback-Leibler divergence metric. We compare the performance of our approach with the well-known aiNet algorithm and find our approach provides a significant improvement on the representation of the final data set.

Original languageEnglish
Title of host publicationArtificial Immune Systems - 10th International Conference, ICARIS 2011, Proceedings
PublisherSpringer Nature
Pages187-197
Number of pages11
ISBN (Print)9783642223709
DOIs
Publication statusPublished - 2011
Event10th International Conference on Artificial Immune Systems, ICARIS 2011 - Cambridge, United Kingdom of Great Britain and Northern Ireland
Duration: 18 Jul 201121 Jul 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6825 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Artificial Immune Systems, ICARIS 2011
Country/TerritoryUnited Kingdom of Great Britain and Northern Ireland
CityCambridge
Period18 Jul 201121 Jul 2011

Fingerprint

Dive into the research topics of 'A lymphocyte-cytokine network inspired algorithm for data analysis'. Together they form a unique fingerprint.

Cite this